Gefei Guan

1.2k total citations · 1 hit paper
29 papers, 762 citations indexed

About

Gefei Guan is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, Gefei Guan has authored 29 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Immunology, 10 papers in Molecular Biology and 10 papers in Genetics. Recurrent topics in Gefei Guan's work include Glioma Diagnosis and Treatment (10 papers), Ferroptosis and cancer prognosis (8 papers) and Immune cells in cancer (6 papers). Gefei Guan is often cited by papers focused on Glioma Diagnosis and Treatment (10 papers), Ferroptosis and cancer prognosis (8 papers) and Immune cells in cancer (6 papers). Gefei Guan collaborates with scholars based in China and United States. Gefei Guan's co-authors include Anhua Wu, Peng Cheng, Wen Cheng, Cunyi Zou, Chen Zhu, Qing Guo, Minghua Zhuang, Weijiang Zhao, Zhiguo Lin and Shuai Shen and has published in prestigious journals such as PLoS ONE, FEBS Letters and Journal of Cellular Physiology.

In The Last Decade

Gefei Guan

29 papers receiving 760 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Ferroptosis, as the most enriched programmed cell death process in glioma, induces immunosuppression and immunotherapy resistance

2022 153 citations Tianqi Liu, Chen Zhu et al. Neuro-Oncology profile →

Peers

Gefei Guan

MB

CR

PRM

IMMUN

ONCOL

Yongshuo Liu China

Khatri Latha United States

Frederick S. Varn United States

Kiek Verrijp Netherlands

Qi-En Wang United States

Eunsohl Lee United States

Tiffany Juarez United States

Zachary A. Kohutek United States

Jonathon Parkinson Australia

Juan M. Funes United Kingdom

Yongshuo Liu China

Gefei Guan

512 ×1.3

MB

204 ×0.7

CR

122 ×0.5

PRM

95 ×0.5

IMMUN

283 ×1.8

ONCOL

Citations per year, relative to Gefei Guan Gefei Guan (= 1×) peers Yongshuo Liu

Countries citing papers authored by Gefei Guan

Since Specialization

Citations

This map shows the geographic impact of Gefei Guan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gefei Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gefei Guan more than expected).

Fields of papers citing papers by Gefei Guan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gefei Guan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gefei Guan. The network helps show where Gefei Guan may publish in the future.

Co-authorship network of co-authors of Gefei Guan

This figure shows the co-authorship network connecting the top 25 collaborators of Gefei Guan. A scholar is included among the top collaborators of Gefei Guan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gefei Guan. Gefei Guan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Cheng, Lin, et al.. (2023). Dissecting multifunctional roles of forkhead box transcription factor D1 in cancers. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1878(6). 188986–188986. 4 indexed citations

2.

Liu, Xing, Qing Guo, Jianqi Wu, et al.. (2023). Tumor microenvironment remodeling plus immunotherapy could be used in mesenchymal-like tumor with high tumor residual and drug resistant rate. Communications Biology. 6(1). 1281–1281. 2 indexed citations

3.

Guo, Qing, Shuai Shen, Gefei Guan, et al.. (2022). Cancer cell intrinsic TIM-3 induces glioblastoma progression. iScience. 25(11). 105329–105329. 33 indexed citations

4.

Chen, Xin, Tianqi Liu, Jianqi Wu, et al.. (2022). Molecular profiling identifies distinct subtypes across TP53 mutant tumors. JCI Insight. 7(23). 8 indexed citations

5.

Liu, Tianqi, Chen Zhu, Xin Chen, et al.. (2022). Ferroptosis, as the most enriched programmed cell death process in glioma, induces immunosuppression and immunotherapy resistance. Neuro-Oncology. 24(7). 1113–1125. 153 indexed citations breakdown →

6.

Zhao, Weijiang, et al.. (2020). A risk signature with four autophagy‐related genes for predicting survival of glioblastoma multiforme. Journal of Cellular and Molecular Medicine. 24(7). 3807–3821. 53 indexed citations

7.

Shen, Shuai, Zihao Yan, Jianqi Wu, et al.. (2020). Characterization of ROS Metabolic Equilibrium Reclassifies Pan-Cancer Samples and Guides Pathway Targeting Therapy. Frontiers in Oncology. 10. 581197–581197. 12 indexed citations

8.

Zhu, Chen, Gefei Guan, Cunyi Zou, et al.. (2020). IFI30 Is a Novel Immune-Related Target with Predicting Value of Prognosis and Treatment Response in Glioblastoma. OncoTargets and Therapy. Volume 13. 1129–1143. 29 indexed citations

9.

Guan, Gefei, Xue Li, Jianqi Wu, et al.. (2020). Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma. Journal of Translational Medicine. 18(1). 378–378. 25 indexed citations

10.

Guan, Shu, Chen Zhu, Qing Guo, et al.. (2020). Secretory Pathway Kinase FAM20C, a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma. OncoTargets and Therapy. Volume 13. 11755–11768. 14 indexed citations

11.

Liu, Xin, et al.. (2019). Identification of a Five-Pseudogene Signature for Predicting Survival and Its ceRNA Network in Glioma. Frontiers in Oncology. 9. 1059–1059. 25 indexed citations

12.

Zou, Cunyi, Chen Zhu, Gefei Guan, et al.. (2019). CD48 is a key molecule of immunomodulation affecting prognosis in glioma. OncoTargets and Therapy. Volume 12. 4181–4193. 26 indexed citations

13.

Zhang, Luyang, Qing Guo, Gefei Guan, et al.. (2019). Integrin Beta 5 Is a Prognostic Biomarker and Potential Therapeutic Target in Glioblastoma. Frontiers in Oncology. 9. 904–904. 33 indexed citations

14.

Liu, Xin, et al.. (2019). A Risk Classification System With Five-Gene for Survival Prediction of Glioblastoma Patients. Frontiers in Neurology. 10. 745–745. 30 indexed citations

15.

Zhao, Weijiang, et al.. (2019). ARL3 is downregulated and acts as a prognostic biomarker in glioma. Journal of Translational Medicine. 17(1). 210–210. 31 indexed citations

16.

Zou, Cunyi, Gefei Guan, Chen Zhu, et al.. (2018). Costimulatory checkpoint SLAMF8 is an independent prognosis factor in glioma. CNS Neuroscience & Therapeutics. 25(3). 333–342. 29 indexed citations

17.

Guo, Qing, Gefei Guan, Wen Cheng, et al.. (2018). Integrated profiling identifies caveolae‐associated protein 1 as a prognostic biomarker of malignancy in glioblastoma patients. CNS Neuroscience & Therapeutics. 25(3). 343–354. 21 indexed citations

18.

Wang, Yulin, Gefei Guan, Wen Cheng, et al.. (2018). ARL2 overexpression inhibits glioma proliferation and tumorigenicity via down-regulating AXL. BMC Cancer. 18(1). 599–599. 24 indexed citations

19.

Guan, Gefei, Mingyi Zhao, Xiaoxue Xu, et al.. (2018). Abnormal changes in voltage-gated sodium channels subtypes Na V 1.1, Na V 1.2, Na V 1.3, Na V 1.6 and CaM/CaMKII pathway in low-grade astrocytoma. Neuroscience Letters. 674. 148–155. 6 indexed citations

20.

Qi, Xun, Yonghui Yuan, Ke Xu, et al.. (2015). (2-Hydroxypropyl)-β-Cyclodextrin Is a New Angiogenic Molecule for Therapeutic Angiogenesis. PLoS ONE. 10(5). e0125323–e0125323. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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